Adjusting for Peer-Influence in Propensity Scoring When Estimating Treatment Effects

46 Pages Posted: 27 Feb 2020 Last revised: 6 Nov 2021

See all articles by Matthew O. Jackson

Matthew O. Jackson

Stanford University - Department of Economics; Santa Fe Institute

Zhongjian Lin

Emory University - Department of Economics

Ning Neil Yu

Nanjing Audit University - Institute for Social and Economic Research

Date Written: January 20, 2020

Abstract

Analyses of treatments, experiments, policies, and observational data, are confounded when people's treatment outcomes and/or participation decisions are influenced by those of their friends and acquaintances. This invalidates standard matching techniques as estimation tools. For instance, the vaccination decisions of a person's peers affect the person's choice to vaccinate as well as the probability that the person is exposed to a disease (violating the usual Stable Unit Treatment Value Assumption). We account for these interferences by explicitly modeling peer interaction in treatment participation decisions and then balance matchings accordingly. We incorporate this approach into one of the most common techniques used to evaluate treatment effects---propensity score matching---and provide asymptotic results. Two applications show that peer-influenced propensity score matching gives more accurate results than standard propensity score matching in the estimation of the effectiveness of vaccinations as well as the impact of
exercise participation on depression.

Keywords: Peer-Influenced Propensity Score Matching (PIPSM); Peer Influence; Propensity Scores; Matched Samples; Matching; Treatment Effect; Influence Network; Peer Effect; Exercise; Depression

JEL Classification: C31; C35; C57; D85, I12

Suggested Citation

Jackson, Matthew O. and Lin, Zhongjian and Yu, Ning Neil, Adjusting for Peer-Influence in Propensity Scoring When Estimating Treatment Effects (January 20, 2020). Available at SSRN: https://ssrn.com/abstract=3522256 or http://dx.doi.org/10.2139/ssrn.3522256

Matthew O. Jackson (Contact Author)

Stanford University - Department of Economics ( email )

Landau Economics Building
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Stanford, CA 94305-6072
United States
1-650-723-3544 (Phone)

HOME PAGE: http://www.stanford.edu/~jacksonm

Santa Fe Institute

1399 Hyde Park Road
Santa Fe, NM 87501
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Zhongjian Lin

Emory University - Department of Economics ( email )

1602 Fishburne Drive
Atlanta, GA 30322
United States

Ning Neil Yu

Nanjing Audit University - Institute for Social and Economic Research ( email )

Stanford, CA 94305
United States

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